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We introduce "smooth diagnosticity." Under smooth diagnosticity, agents over-react to new information defined as the difference between the current information set and a previous information set. Since new information typically changes not just the conditional mean, but also the conditional uncertainty, changes in uncertainty surrounding current and past beliefs affect the severity of the Diagnostic Expectations (DE) distortion. Smooth DE nests the baseline DE of Bordalo et al. (2018) and implies a joint and parsimonious micro-foundation for various properties of survey data: (1) over-reaction of conditional mean to news, (2) stronger over-reaction for weaker signals and longer forecast horizons, and (3) over-confidence in subjective uncertainty. We embed Smooth DE in an analytical RBC model. The model accounts for over-reaction and over-confidence in surveys, as well as three salient properties of the business cycle: (1) asymmetry, (2) countercyclical micro volatility, and (3) countercyclical macro volatility